• E. Jin, Q. Feng, Y. Mou, G. Lakemeyer, S. Decker, O. Simons, J. Stegmaier, “LogicAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction”, AAAI Conference on Artificial Intelligence, Philadelphia (USA), Feb 25 - Mar 4, 2025.
• Y. Wu, D. D. T. Nguyen, H. Konermann, R. Yilmaz, P. Walter, J. Stegmaier, “Visual Fixation-Based Retinal Prosthetic Simulation”, IEEE International Symposium on Biomedical Imaging, Houston (USA), Apr 14-17, 2025.
• R. Yilmaz, K. Keven, Y. Wu, J. Stegmaier, “Cascaded Diffusion Models for 2D and 3D Microscopy Image Synthesis t o Enhance Cell Segmentation”, IEEE International Symposium on Biomedical Imaging, Houston (USA), Apr 14-17, 2025.
• F. Javadian, Z. Aminparast, J. Stegmaier, A. Jose, “Sensitivity Analysis of Nuclei-Grading Impact on Patch-Level Predictions for Grading CCRCC”, IEEE International Symposium on Biomedical Imaging, Houston (USA), Apr 14-17, 2025.
• E. Mededovic, V. Laurentius, Y. Wu, M. Kopaczka, Z. Chen, M. Schulz, R. Tolba, J. Stegmaier, “No Free Lunch in Annotation Either: An Objective Evaluation of Foundation Models for Streamlining Annotation in Animal Tracking”, IEEE International Symposium on Biomedical Imaging, Houston (USA), Apr 14-17, 2025.
• Y. Zhang, E. Jin, Y. Dong, P. Torr, J. Stegmaier, K. Kawaguchi, “Effortless Efficiency: Low-Cost Pruning of Diffusion Models”, SCOPE Workshop at the International Conference on Learning Representations, Singapore, Apr 24 - 28, 2025.

• D. Eschweiler, R. Yilmaz, M. Baumann, I. Laube, D. Brückner, J. Stegmaier, “Denoising Diffusion Probabilistic Models for Generation of Realistic Fully-Annotated Microscopy Image Data Sets”, PLOS Computational Biology, e1011890, 2024.
• K. Gordiyenko, A. Angelin, S. Weigel, R. Garrecht, A. Schipperges, R. Kumar, M. Hirtz, R. Mikut, M. Reischl, J. Stegmaier, L. Zhou, R. Ma, G. U. Nienhaus, K. S. Rabe, C. M. Domínguez, C. M. Niemeyer, “Surface-Patterned DNA Origami Rulers Reveal Nanoscale Distance-Dependency of the Epidermal Growth Factor Receptor Activation”, Nano Letters, 24(5), pp. 1611—1619, 2024.
• A. Jose, R. Roy, D. Moreno-Andrés, J. Stegmaier, “Automatic Detection of Cell-cycle Stages using Recurrent Neural Networks”, PLOS ONE, 19(3), e0297356, 2024.
• Y. Wu, W. He, D. Eschweiler, S. Mi, P. Walter, J. Stegmaier, “Retinal OCT Synthesis with Denoising Diffusion Probabilistic Models for Layer Segmentation”, IEEE International Symposium on Biomedical Imaging, Athens (Greece), May 27-30, 2024.
• M. A. Aziz, F. Javadian, A. Gopal, S. S. Mathew, J. Stegmaier, A. Jose, “Deep Learning Approach for Renal Cell Carcinoma Detection and Grading”, IEEE International Conference on Image Processing, Abu Dhabi (United Arab Emirates), October 27-30, 2024.
• R. Yilmaz, D. Eschweiler, J. Stegmaier, “Flow-based Annotated Cellular Video Generation with Denoising Diffusion Probabilistic Models”, International Workshop on Simulation and Synthesis in Medical Imaging, Marakesh (Morocco), October 6-10, 2024.

• F. Khader, G. Müller-Franzes, T. Wang, T. Han, S. T. Arasteh, C. Haarburger, J. Stegmaier, K. Bressem, C. Kuhl, S. Nebelung, J. N. Kather, D. Truhn, “Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters - A Case for Transformers”, Radiology, 309(1), e230806, 2023.
• F. Khader, J. N. Kather, G. Müller-Franzes, T. Wang, T. Han, S. T. Arasteh, K. Hamesch, K. Bressem, C. Haarburger, J. Stegmaier, C. Kuhl, S. Nebelung, D. Truhn, “Medical Transformer for Multimodal Survival Prediction in Intensive Care – Integration of Image and Clinical Data”, Scientific Reports, 13(1), 10666, 2023.
• F. Khader, G. Müller-Franzes, S. T. Arasteh, T. Han, C. Haarburger, M. Schulze-Hagen, S. Engelhardt, B. Baeßler, S. Foersch, J. Stegmaier, C. Kuhl, S. Nebelung, J. N. Kather, D. Truhn, “Denoising Diffusion Probabilistic Models for 3D Medical Image Generation”, Scientific Reports, 13(1), 7303, 2023.
• A. Dievernich∗, J. Stegmaier∗, P. Achenbach, S. Warkentin, T. Braunschweig, U. P. Neumann, U. Klinge , “A Deep Learning-Computed Cancer Score for the Identification of Human Hepatocellular Carcinoma Area based on a Six-Colour Multiplex Immunofluorescence Panel”, Cells, 12(7), 1074, 2023.
• S. Hermans, J. Pilon, D. Eschweiler, J. Stegmaier, C. Severens-Rijvers, S. Al-Nasiry, M. v. Zandvoort, D. Kapsokalyvas, “Definition and Quantification of 3-Dimensional Imaging Targets to Phenotype Pre-Eclampsia Subtypes: An Exploratory Study”, International Journal of Molecular Sciences, 24(4), 3240, 2023.
• L. Chen, Y. Wu, J. Stegmaier, D. Merhof, “SortedAP: Rethinking Evaluation Metrics for Instance Segmentation”, Bioimage Computing Workshop, Paris (France), October 3, 2023.
• T. Rehbronn, R. v. Kempen, A. Jose, J. Stegmaier, L. Eckstein, “Enhancing Lidarbased Object Detection in Adverse Weather using Offset Sequences in Time”, The 3rd International Conference on Electrical, Computer and Energy Technologies, Cape Town (South Africa), November 16-17, 2023.
• F. Khader, J. Stegmaier, S. Nebelung, D. Truhn, “Multi-View Abnormality Detection in Clinical Knee MRI Studies using Transformers”, IEEE International Symposium on Biomedical Imaging, Cartagena de Indias (Colombia), April 18-21, 2023.
• F. Khader, J. Kather, T. Han, S. Nebelung, C. Kuhl, J. Stegmaier, D. Truhn, “Cascaded Cross Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers”, Machine Learning in Medical Imaging, Vancouver (CA), October 8, 2023.
• F. Khader, G. Müller-Franzes, T. Han, S. Nebelung, C. Kuhl, J. Stegmaier, D. Truhn, “Transformers for CT Reconstruction From Monoplanar and Biplanar Radiographs”, International Workshop on Simulation and Synthesis in Medical Imaging, 2023.
• F. Khader, G. Müller-Franzes, S. T. Arasteh, T. Han, J. N. Kather, C. Kuhl, J. Stegmaier, S. Nebelung, D. Truhn, “Vector Quantized Latent Flows for Medical Image Synthesis and Out-of-Distribution Detection”, IEEE International Symposium on Biomedical Imaging, Cartagena de Indias (Colombia), April 18-21, 2023.
• Z. Chen∗, I. Laube∗, J. Stegmaier, “Unsupervised Learning for Feature Extraction and Temporal Alignment of 3D+t Point Clouds of Zebrafish Embryos”, Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver (CA), October 8-12, 2023.
• Y. Wu, I. Karetic, J. Stegmaier, P. Walter, D. Merhof, “A Deep Learning-based in silico Framework for Optimization on Retinal Prosthetic Stimulation”, 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Sydney (Australia), July 24-27, 2023.
• A. Jose, R. Roy, J. Stegmaier, “Weakly-supervised Temporal Segmentation of Cellcycle Stages with Center-Cell Focus using Recurrent Neural Networks”, Bildverarbeitung für die Medizin, Braunschweig (Germany), July 2-4, 2023.
• A. Jose, R. Roy, D. Eschweiler, I. Laube, R. Azad, D. Moreno-Andrés, J. Stegmaier, “End-to-End Classification of Cell-Cycle Stages with Center-Cell Focus Tracker using Recurrent Neural Networks”, IEEE International Conference on Acoustics, Speech, and Signal Processing, Rhodes Island (Greece), June 4-10, 2023.

(*) Equal contribution.

• S. Strauss, A. Runions, B. Lane, D. Eschweiler, N. Bajpai, N. Trozzi, A. L. Routier-Kierzkowska, S. Yoshida, S. d. Rodrigues, A. Vijayan, R. Tofanelli, M. Majda, E. Echevin, C. Le Gloanec, H. Bertrand-Rakusova, M. Adibi, K. Schneitz, G. Bassel, D. Kierzkowski, J. Stegmaier, M. Tsiantis, R. S. Smith, “Using Positional Information to Provide Context for Biological Image Analysis with MorphoGraphX 2.0”, eLife, 11, 2022.
• R. Windoffer, N. Schwarz, S. Yoon, T. Piskova, M. Scholkemper, J. Stegmaier, A. Bönsch, J. D. Russo, R. E. Leube, “Quantitative Mapping of Keratin Networks in 3D”, eLife, 11, e75894, 2022.
• F. Khader, T. Han, G. Müller-Franzes, L. Huck, P. Schad, S. Keil, E. Barzakova, M. Schulze-Hagen, F. Pedersoli, L. Nebelung, J. Kather, K. Hamesch, C. Haarburger, J. Stegmaier, C. Kuhl, P. Bruners, S. Nebelung, D. Truhn, “Artificial Intelligence for Clinical Interpretation of Bedside Chest Radiographs”, Radiology, 220510, 2022.
• D. Moreno-Andrés, A. Bhattacharyya, A. Scheufen, J. Stegmaier, “LiveCellMiner: A New Tool to Analyze Mitotic Progression”, PLOS ONE, 17(7), e0270923, 2022.
• D. Eschweiler, I. Laube, J. Stegmaier, “Spatiotemporal Image Generation for Embryomics Applications”, Biomedical Image Synthesis and Simulation: Methods and Applications, pp. 517–541, 2022.
• U. Klinge, A. Dievernich, J. Stegmaier, “Quantitative Characterization of Macrophage, Lymphocyte and Neutrophil Subtypes within the Foreign Body Granuloma of Human Mesh Explants by 5-Marker Multiplex Fluorescence Microscopy”, Frontiers in Medicine, 9, 777439, 2022.
• A. Jose, Q. Mei, D. Eschweiler, I. Laube, J. Stegmaier, “Linear Discriminant Analysis Metric Learning using Siamese Neural Networks”, IEEE International Conference in Image Processing, Bordeaux (France), 2022.
• D. Eschweiler, R. S. Smith, J. Stegmaier, “Robust 3D Cell Segmentation: Extending the View of Cellpose”, IEEE International Conference in Image Processing, Bordeaux (France), 2022.
• D. Eschweiler, J. Schock, J. Stegmaier, “Probabilistic Image Diversification to Improve Segmentation in 3D Microscopy Image Data”, International Workshop on Simulation and Synthesis in Medical Imaging, Singapur, September 18, 2022.
• F. Khader, C. Haarburger, J.-C. Kirr, M. Menke, J. Stegmaier, C. Kuhl, S. Nebelung, D. Truhn, “Elevating Fundoscopic Evaluation to Expert Level-Automatic Glaucoma Detection Using Data from the Airogs Challenge”, IEEE International Symposium on Biomedical Imaging Challenges, Kolkata (India), March 28-31, 2022.

• Y.-F. Zhang, L. V. Cifuentes, K. N. Wright, J. P. Bhattarai, J. Mohrhardt, D. Fleck, E. Janke, C. Jiang, S. L. Cranfill, N. Goldstein, M. Schreck, A. H. Moberly, Y. Yu, B. R. Arenkiel, J. N. Betley, W. Luo, J. Stegmaier, D. W. Wesson, M. Spehr, M. V. Fuccillo, M. Ma, “Ventral Striatal Islands of Calleja Neurons Control Grooming in Mice”, Nature Neuroscience, 24(12), pp. 1699–1710, 2021.
• S. Bhide, D. Gombalova, J. Stegmaier, G. Mönke, J. M. Belmonte, M. Leptin, “Mechanical Competition Alters the Cellular Interpretation of an Endogenous Genetic Programme”, Journal of Cell Biology, 220(11), e202104107, 2021.
• S. Rubin, A. Agrawal, J. Stegmaier, J. Svorai, Y. Addadi, P. Villoutreix, T. Stern, E. Zelzer, “3D MAPs Discovers the Morphological Sequence Chondrocytes Undergo in the Growth Plate and the Regulatory Role of GDF5 in this Process”, Nature Communications, 12(1), pp. 1—16, 2021.
• D. Eschweiler, M. Rethwisch, M. Jarchow, S. Koppers, J. Stegmaier, “3D Fluorescence Microscopy Data Synthesis for Segmentation and Benchmarking”, PLOS ONE, 16(12), e0260509, 2021.
• C. Yang, D. Eschweiler, J. Stegmaier, “Semi- and Self-Supervised Multi-View Fusion of 3D Microscopy Images using Generative Adversarial Networks”, Machine Learning for Medical Image Reconstruction, Strasbourg (France), October 1, 2021.
• D. Bähr, D. Eschweiler, A. Battacharyya, D. Moreno-Andrés, W. Antonin, J. Stegmaier, “CellCycleGAN: Spatiotemporal Microscopy Image Synthesis of Cell Populations using Statistical Shape Models and Conditional GANs”, IEEE International Symposium on Biomedical Imaging, Nice (France), April 13-16, 2021.
• D. Eschweiler, M. Rethwisch, S. Koppers, J. Stegmaier, “Spherical Harmonics for Shape-Constrained 3D Cell Segmentation”, IEEE International Symposium on Biomedical Imaging, Nice (France), April 13-16, 2021.

• T. Scherr, K. Streule, A. Bartschat, M. Böhland, K. Löffler, J. Stegmaier, M. Reischl, V. Orian-Rousseau, R. Mikut, “BeadNet: Automated Bead Detection and Counting in Low-Resolution Microscopy Images”, Bioinformatics, 36(17), pp. 4668–4670, 2020.
• M. Takamiya, J. Stegmaier, A. Y. Kobitski, B. Schott, B. D. Weger, D. Margariti, A. R. C. Delgado, V. Gourain, T. Scherr, L. Yang, S. Sorge, V. Hartmann, J. C. Otte, J. v. Wezel, R. Stotzka, T. Reinhard, G. Schlunk, T. Dickmeis, S. Rastegar, R. Mikut, G. U. Strähle, “Pax6 Organizes the Anterior Eye Segment Independently of Optic Cup Patterning by Guiding Two Distinct Neural Crest Waves”, PLOS Genetics, 16(6), e1008774, 2020.
• J. Gierten, C. Pylatiuk, O. T. Hammouda, C. Schock, J. Stegmaier, J. Wittbrodt, J. Gehrig, F. Loosli, “Automated High-Throughput Heartbeat Quantification in Medaka and Zebrafish Embryos under Physiological Conditions”, Scientific Reports, 10(1), 2046, 2020.
• N. Kumar, R. Verma, D. Anand, Y. Zhou, [...], D. Eschweiler, J. Stegmaier, Y. Cui, [...], Y. Wang, A. Sethi, “A Multi-Organ Nucleus Segmentation Challenge”, IEEE Transactions on Medical Imaging, 39(5), pp. 1380—1391, 2020.
• M. Weger, B. D. Weger, A. Schink, M. Takamiya, J. Stegmaier, C. Gobet, A. Parisi, A. Y. Kobitski, J. Mertes, N. Krone, U. Strähle, G. U. Nienhaus, R. Mikut, F. Gachon, P. Gut, T. Dickmeis, “MondoA Regulates Gene Expression in Cholesterol Biosynthesis-Associated Pathways Required for Zebrafish Epiboly”, eLife, 9, e57068, 2020.
• S. Bhide, R. Mikut, M. Leptin, J. Stegmaier, “Semi-Automatic Generation of Tight Binary Masks and Non-Convex Isosurfaces for Quantitative Analysis of 3D Biological Samples”, IEEE International Conference on Image Processing, Abu Dhabi (United Arab Emirates), October 25-28, 2020.
• M. Traub, J. Stegmaier, “Towards Automatic Embryo Staging in 3D+T Microscopy Images using Convolutional Neural Networks and PointNets”, International Workshop on Simulation and Synthesis in Medical Imaging, Lima (Peru), October 4, 2020.

• A. Bartschat, S. Allgeier, T. Scherr, J. Stegmaier, S. Bohn, K.-M. Reichert, A. Kuijper, M. Reischl, O. Stachs, B. Köhler, R. Mikut, “Fuzzy Tissue Detection for Real-Time Focal Control in Corneal Confocal Microscopy”, at Automatisierungstechnik, 67(19), pp. 879–888, 2019.
• M. Grösche, A. E. Zoheir, J. Stegmaier, R. Mikut, D. Mager, J. G. Korvink, K. S. Rabe, C. M. Niemeyer, “Microfluidic Chips for Life Sciences: A Comparison of Low Entry Manufacturing Technologies”, Small, 15(35), 1901956, 2019.
• V. Gerber, L. Yang, M. Takamiya, V. Ribes, V. Gourain, R. Peravali, J. Stegmaier, R. Mikut, M. Reischl, M. Ferg, S. Rastegar, U. Strähle, “The HMG Box Transcription Factors Sox1a and b Specify a New Class of Glycinergic Interneurons in the Spinal Cord of Zebrafish Embryos”, Development, 146(4), dev172510, 2019.
• D. Eschweiler, T. Klose, F. N. Müller-Fourage, M. Kopaczka, J. Stegmaier, “Towards Annotation-Free Segmentation of Fluorescently Labeled Cell Membranes in Confocal Microscopy Images”, International Workshop on Simulation and Synthesis in Medical Imaging, Shenzhen (China), October 13, 2019.
• D. Bug, D. Eschweiler, Q. Liu, J. Schock, L. Weniger, F. Feuerhake, J. Schüler, J. Stegmaier, D. Merhof, “Combined Learning for Similar Tasks with Domain-Switching Networks”, Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen (China), October 13-17, 2019.
• D. Eschweiler, T. V. Spina, R. C. Choudhury, E. Meyerowitz, A. Cunha, J. Stegmaier, “CNN-based Preprocessing to Optimize Watershed-based Cell Segmentation in 3D Confocal Microscopy Images”, IEEE International Symposium on Biomedical Imaging, Venice (Italy), April 8-11, 2019.

• V. Bedell, E. Buglo, D. Marcato, C. Pylatiuk, R. Mikut, J. Stegmaier, W. Scudder, M. Wray, S. Züchner, U. Strähle, R. Peravali, J. E. Dallman, “Zebrafish: A Pharmacogenetic Model for Anesthesia”, Methods in Enzymology, 602, pp. 189—209, 2018.
• B. Schott, M. Traub, C. Schlagenhauf, M. Takamiya, T. Antritter, A. Barschat, K. Löffler, D. Blessing, J. C. Otte, A. Kobitski, G. U. Nienhaus, U. Strähle, R. Mikut, J. Stegmaier, “EmbryoMiner: A New Framework for Interactive Knowledge Discovery in Large-Scale Cell Tracking Data of Developing Embryos”, PLOS Computational Biology, 14(4), e1006128, 2018.
• H. M. T. Choi, M. Schwarzkopf, M. E. Fornace, A. Acharya, G. Artavanis, J. Stegmaier, A. Cunha, N. A. Pierce, “Third-Generation In Situ Hybridization Chain Reaction: Multiplexed, Quantitative, Sensitive, Versatile, Robust”, Development, 145(12), 2018.
• B. Mattes, Y. Dang, G. Greicius, L. T. Kaufmann, S. Özbek, B. Prunsche, J. Rosenbauer, J. Stegmaier, R. Mikut, G. U. Nienhaus, A. Schug, D. M. Virshup, S. Scholpp, “Wnt/PCP Controls Spreading of Wnt/β-Catenin Signals by Cytonemes in Vertebrates”, eLife, 7, e36953, 2018.
• J. Stegmaier, T. V. Spina, A. Falc ao, A. Bartschat, R. Mikut, E. Meyerowitz, A. Cunha, “Cell Segmentation in 3D Microscopy Images using Supervoxel Merge-Forests with CNN-based Hypothesis Selection”, IEEE International Symposium on Biomedical Imaging, Washington D.C. (USA), April 4-7, 2018.
• T. V. Spina, J. Stegmaier, A. Falc ao, E. Meyerowitz, A. Cunha, “SEGMENT3D: A Web-based Application for Collaborative Segmentation of 3D Images used in the Shoot Apical Meristem”, IEEE International Symposium on Biomedical Imaging, Washington D.C. (USA), April 4-7, 2018.

• J. Stegmaier, R. Mikut, “Fuzzy-based Propagation of Prior Knowledge to Improve Large-Scale Image Analysis Pipelines”, PLOS ONE, 12(11), e0187535, 2017.
• V. Ulman, M. Maška, K. Magnusson, O. Ronneberger, C. Haubold, N. Harder, P. Matula, P. Matula, D. Svoboda, M. Radojevic, I. Smal, K. Rohr, J. Jaldén, H. Blau, O. Dzyubachyk, B. Lelieveldt, P. Xiao, Y. Li, S. Cho, A. Dufour, J. Olivo-Marin, C. Reyes-Aldasoro, J. Solis-Lemus, R. Bensch, T. Brox, J. Stegmaier, R. Mikut, S. Wolf, F. Hamprecht, T. Esteves, P. Quelhas, Ö. Demirel, L. Malmström, F. Jug, P. Tomančák, E. Meijering, A. Mu noz-Barrutia, M. Kozubek, C. Ortiz-de-Solórzano, “An Objective Comparison of Cell Tracking Algorithms”, Nature Methods, 14(12), pp. 1141–1152, 2017.
• C. Etard, S. Joshi, J. Stegmaier, R. Mikut, U. Strähle, “TIDE is a Simple and Effective Method to Assess Efficiency of Guide RNAs in Zebrafish”, Zebrafish, 14(6), pp. 586–588, 2017.
• A. Bartschat, J. Stegmaier, S. Allgeier, K. M. Reichert, S. Bohn, O. Stachs, B. Köhler, R. Mikut, “Augmentations of the Bag of Visual Words Approach for Real-Time Fuzzy and Partial Image Classification”, 27. Workshop Computational Intelligence, Dortmund, Dortmund, November 23-24, 2017.

• A. Bartschat, E. Hübner, M. Reischl, R. Mikut, J. Stegmaier, “XPIWIT - An XML Pipeline Wrapper for the Insight Toolkit”, Bioinformatics, 32(2), pp. 315–317, 2016.
• J. Stegmaier, F. Amat, B. Lemon, K. McDole, Y. Wan, G. Teodoro, R. Mikut, P. J. Keller, “Real-Time Three-Dimensional Cell Segmentation in Large-Scale Microscopy Data of Developing Embryos”, Developmental Cell, 36(2), pp. 225–240, 2016.
• J. Stegmaier, B. Schott, E. Hübner, M. Traub, M. Shahid, M. Takamiya, A. Kobitski, V. Hartmann, R. Stotzka, J. v. Wezel, A. Streit, G. U. Nienhaus, U. Strähle, M. Reischl, R. Mikut, “Automation Strategies for Large-Scale 3D Image Analysis”, at Automatisierungstechnik, 64(7), pp. 555–566, 2016.
• M. Shahid∗, M. Takamiya∗, J. Stegmaier∗, V. Middel, N. Klüver, R. Mikut, S. Rastegar, S. Scholz, T. Dickmeis, L. Yang, U. Strähle, “Zebrafish Biosensor for Toxicant Induced Muscle Hyperactivity”, Scientific Reports, 6(1), 23768, 2016.
• A. Bartschat, L. Toso, J. Stegmaier, A. Kuijper, R. Mikut, B. Köhler, S. Allgeier, “Automatic Corneal Tissue Classification Using Bag-of-Visual-Words Approaches”, Forum Bildverarbeitung, Karlsruhe, December 1-2, 2016.
• J. Stegmaier, N. Peter, J. Portl, I. Mang, H. Leitte, R. Mikut, M. Reischl, “A Framework for Feedback-based Segmentation of 3D Image Stacks”, Current Directions in Biomedical Engineering, 2(1), pp. 437–441, 2016.
• J. Stegmaier, J. Arz, B. Schott, J. C. Otte, A. Kobitski, G. U. Nienhaus, U. Strähle, P. Sanders, R. Mikut, “Generating Semi-Synthetic Validation Benchmarks for Embryomics”, IEEE International Symposium on Biomedical Imaging, Prague (Czech Republic), April 13-16, 2016.
• B. Schott, J. Stegmaier, A. Arbaud, M. Reischl, R. Mikut, F. Lévi, “Robust Individual Circadian Parameter Estimation for Biosignal-based Personalization of Cancer Chronotherapy”, Workshop Biosignal Processing, Berlin, April 7-8, 2016.

(*) Equal contribution.

• A. Kobitski, J. C. Otte, M. Takamiya, B. Schäfer, J. Mertes, J. Stegmaier, S. Rastegar, F. Rindone, V. Hartmann, R. Stotzka, A. García, J. v. Wezel, R. Mikut, U. Strähle, G. U. Nienhaus, “An Ensemble- averaged Digital Model of Zebrafish Embryo Development based on High-Speed Light-Sheet Microscopy at Single-Cell Resolution”, Scientific Reports, 5, 8601, 2015.
• B. Schott, J. Stegmaier, M. Takamiya, R. Mikut, “Challenges of Integrating A Priori Information Efficiently in the Discovery of Spatio-Temporal Objects in Large Databases”, 25. Workshop Computational Intelligence, Dortmund, 2015.
• J. Portl, J. Stegmaier, I. V. Mang, M. Reischl, R. Schröder, H. Leitte, “Visualization for Error-controlled Surface Reconstruction from Large Electron Microscopy Image Stacks”, IEEE Vis, Chicago, Illinois (USA), October 25-30, 2015.

• J. Stegmaier, J. C. Otte, A. Kobitski, A. Bartschat, A. Garcia, G. U. Nienhaus, U. Strähle, R. Mikut, “Fast Segmentation of Stained Nuclei in Terabyte-Scale, Time Resolved 3D Microscopy Image Stacks”, PLOS ONE, 9(2), e90036, 2014.
• J. Stegmaier∗, M. Shahid∗, M. Takamiya, L. Yang, S. Rastegar, M. Reischl, U. Strähle, R. Mikut, “Automated Prior Knowledge-Based Quantification of Neuronal Patterns in the Spinal Cord of Zebrafish”, Bioinformatics, 30(5), pp. 726–733, 2014.

(*) Equal contribution.

• J. Stegmaier, D. Skanda, D. Lebiedz, “Robust Optimal Design of Experiments for Model Discrimination using an Interactive Software Tool”, PLOS ONE, 8, e55723, 2013.

• J. Stegmaier, A. Khan, M. Reischl, R. Mikut, “Challenges of Uncertainty Propagation in Image Analysis”, 22. Workshop Computational Intelligence, Dortmund, December 6-7, 2012.
• J. Stegmaier, R. Alshut, M. Reischl, R. Mikut, “Information Fusion of Image Analysis, Video Object Tracking, and Data Mining of Biological Images using the Open Source MATLAB Toolbox Gait-CAD”, Biomedizinische Technik, 57, pp. 458–461, 2012.